ProfessorsProfessors of Pohang University of Science and TechnologySeungjin Choi

Seungjin Choi

Pohang University of Science and Technology

H-index: 54

Asia-South Korea

About Seungjin Choi

Seungjin Choi, With an exceptional h-index of 54 and a recent h-index of 29 (since 2020), a distinguished researcher at Pohang University of Science and Technology, specializes in the field of machine learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

BayesO: A Bayesian optimization framework in Python

Unsupervised learning

Combinatorial Bayesian optimization with random mapping functions to convex polytopes

On uncertainty estimation by tree-based surrogate models in sequential model-based optimization

Bayesian optimization with approximate set kernels

Meta-learning: Towards fast adaptation in multi-subject eeg classification

Sparse network inversion for key instance detection in multiple instance learning

On local optimizers of acquisition functions in bayesian optimization

Seungjin Choi Information

University	Pohang University of Science and Technology
Position	Professor of Computer Science
Citations(all)	10939
Citations(since 2020)	4563
Cited By	18354
hIndex(all)	54
hIndex(since 2020)	29
i10Index(all)	163
i10Index(since 2020)	72
Email	Access Email
University Profile Page	Pohang University of Science and Technology
Google Scholar	View Google Scholar Profile

Seungjin Choi Skills & Research Interests

machine learning

Top articles of Seungjin Choi

Title	Journal	Author(s)	Publication Date
BayesO: A Bayesian optimization framework in Python	Journal of Open Source Software	Jungtaek Kim Seungjin Choi	2023
Unsupervised learning	Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications	Laura Igual Santi Seguí Laura Igual Santi Seguí	2017
Combinatorial Bayesian optimization with random mapping functions to convex polytopes		Jungtaek Kim Seungjin Choi Minsu Cho	2022/8/17
On uncertainty estimation by tree-based surrogate models in sequential model-based optimization		Jungtaek Kim Seungjin Choi	2022/5/3
Bayesian optimization with approximate set kernels	Machine Learning	Jungtaek Kim Michael McCourt Tackgeun You Saehoon Kim Seungjin Choi	2021/5
Meta-learning: Towards fast adaptation in multi-subject eeg classification		Seungjin Choi	2021/2/22
Sparse network inversion for key instance detection in multiple instance learning		Beomjo Shin Junsu Cho Hwanjo Yu Seungjin Choi	2021/1/10
On local optimizers of acquisition functions in bayesian optimization		Jungtaek Kim Seungjin Choi	2020/9/16
Neural complexity measures	Advances in Neural Information Processing Systems	Yoonho Lee Juho Lee Sung Ju Hwang Eunho Yang Seungjin Choi	2020